KR101615747B1 - A efficient improvement method for maximum power point tracking of the solar inverter in case of partial shading - Google Patents

Abstract

The present invention relates to a method for improving MPPT efficiency of a solar inverter in case of partial shading. The method comprises: step (a) of following a maximum power point until a change of current power becomes smaller than a preset first threshold value; step (b) of randomly generating speed of each particle; step (c) of calculating or updating an optimized location per a particle and the total optimized location in accordance with conformity; step (d) of calculating or updating the total optimized location with the best conformity in a mutant particle group; and step (e) of performing step (a) in case of a predetermined condition while alternately and repetitively performing step (c) and step (d). Therefore, even though shading occurs, the maximum power point can be always followed.

Description

[0001] The present invention relates to a method of improving MPPT efficiency of a photovoltaic inverter in partial shading,

In performing MPPT control of a solar inverter at partial shading, the present invention performs a Perturbation and Observation (P & O) control method in which an output voltage is periodically increased or decreased. When following a local maximum power point, The present invention relates to a method for improving the MPPT efficiency of a solar photovoltaic inverter at partial shading by performing a DEPSO (Differential Evolution and Particle Swarm Optimization) method so as to follow the maximum power point at another local position.

Global warming and energy policies have recently become international agendas and developed countries are trying to reduce greenhouse gas emissions. In this situation, solar power generation is semi-permanent, it is easy to maintain using solar cell, and because it uses unlimited, no-limit solar energy source, it is becoming a future alternative energy source. After installing solar power, it will produce electricity according to solar radiation without emitting greenhouse gas. However, facilities for photovoltaic power generation have a high initial investment cost. By increasing the efficiency of solar power generation, profitability of solar power generation can be increased.

The efficiency of solar power generation is largely influenced by three factors. Efficiency of the PV (Photovoltaic) panel, efficiency of the inverter, and efficiency of the maximum power point tracking (MPPT) algorithm. Following this, it is easier and less costly to follow the maximum power point (MPP) with the new control algorithm than to increase the other efficiency.

The PV array requires the MPPT algorithm because it has a non-linear voltage-current characteristic with a unique point at which the generated power is at its maximum. The maximum power point (MPP) depends on the temperature of the panel and the solar radiation conditions. Both conditions change day by day and depend on the season. In addition, solar radiation can change rapidly because it changes with the state of the atmosphere, such as clouds. It is very important to accurately track the MPP under all possible conditions to always get the maximum power point.

Therefore, technologies that follow the maximum power point (MPP) are being proposed. Techniques for following the maximum power point (MPP) include a Perturbation and Observation (P & O) control method, an incremental conductance (InCond) control method, and a Hill Climbing control method.

The P & O control method is a method of periodically increasing or decreasing the output voltage of the solar cell array, comparing the previous output power with the present output power to find the maximum power operating point, and the incremental conductance control method is to determine the conductance of the solar cell output And the incremental conductance is compared to find the maximum power operating point. The hill climbing control is a method of following the maximum power point by adding or subtracting the duty ratio.

As one example of the P & O control method, techniques for following the maximum power point through an instantaneous change amount of the output power (P) of the solar cell array according to the change of the output voltage (V) of the solar cell array are proposed [Patent Document 1] . At this time, the voltage increment is added to or subtracted from the output voltage of the solar cell array module, and the output power of the added / subtracted output voltage is controlled to be the maximum. Although the P & O control technique is not complicated, the control technique can increase or decrease the voltage increment value with respect to a specific voltage value, and thus vibration occurs in the power value near the maximum power point, resulting in power loss.

Further, according to the P & O control method according to the related art, the characteristic is changed according to the magnitude? V of the reference voltage fluctuation width. When? V is large, the MPP follow-up speed is increased but the output voltage fluctuation width is widened. On the contrary, when? V is small, the MPP follow-up speed is reduced, but the advantage is that the fluctuation range of the output voltage is narrowed.

In order to solve such a problem, a technique of using a variable value of voltage increment has been proposed [Patent Document 2]. However, in the Patent Document 2, only the variable voltage increment is varied only by the value for the previous voltage increment or the output power increment. That is, in Patent Document 2, no consideration is given to an element for current.

Further, according to the P & O control method according to the related art, since the current voltage is increased or decreased, the resulting maximum power point can be the maximum power point in the region that is not the maximum power point in the whole. This phenomenon occurs when a shadow area occurs on a solar panel. That is, when there are a plurality of local maximum points on the graph of voltage and power, there occurs a problem of finding the maximum power point at a local position lower than the entire maximum power point as a final power point.

Korean Registered Patent No. 10-1065862 (Announced on September 20, 2011) Korean Registered Patent No. 10-1223611 (published on Jan. 17, 2013)

SUMMARY OF THE INVENTION An object of the present invention is to solve the above problems and to provide a Perturbation and Observation (P & O) control method for periodically increasing or decreasing an output voltage in performing MPPT control of a solar inverter at partial shading, If the local maximum power point is followed, MPPT of partial solar photovoltaic inverters, which follow the maximum power point of other local locations by performing differential evolution and particle swarm optimization (DEPSO) And to provide a method for improving efficiency.

In order to achieve the above object, the present invention relates to a method for improving the MPPT efficiency of a solar inverter in partial shading of a string and an array of solar panels, comprising the steps of: (a) following a maximum power point by P & Following the convergence to an arbitrary point until the change of the current power is smaller than a predetermined first threshold value; (b) generating a population of particles of N particles by composing the correction voltage as particles, and randomly generating the speed of each particle; (c) updating the velocity of each particle to find a moving position, calculating a fitness at a position of each particle, and calculating or updating an optimal position and a total optimum position for each particle according to the fitness; (d) randomly selecting at least three particles in the population of particles, generating a mutation vector for the selected particles, generating a population of mutant particles containing a mutation vector according to the random variable, Calculating or updating a total optimum position that is the best; (e) repeating the steps (c) and (d), and repeating the steps (a) and (d), wherein the number of repetitions exceeds a preset number of times, And if the optimal position is detected, performing the step (a).

Further, the present invention is a method for improving MPPT efficiency of a solar inverter in partial shading, wherein a position of each particle in the particle group is set as a correction voltage, and a fitness of each particle is measured when the correction voltage is a position of each particle Power is set.

Further, the present invention provides a method for improving the MPPT efficiency of a solar inverter in partial shading, wherein in the step (c) or (d), the fitness according to the previous position, If the ratio of the difference in fitness by the second threshold is greater than a second threshold value determined in advance, the step (b) is repeated to repeat.

The present invention also provides a method for improving MPPT efficiency of a solar photovoltaic inverter in partial shading, the method comprising: calculating current power by measuring a current voltage and a current current in step (a), calculating a voltage increment, The voltage increment is added to calculate the correction voltage of the next turn, and the power of the next turn is calculated and repeated by the calculated correction voltage to obtain the power change.

Further, the present invention is a method for improving MPPT efficiency of a solar photovoltaic inverter in partial shading, characterized in that the sign of the voltage increment is determined according to the result of comparing the current power with the previous power in the step (a).

The present invention is part of the sun improved MPPT efficiency of the optical drive method at the time of shading, but in the step (b), the initialization of, population and velocity of the particles by the following equation 1, V _j ⁱ is the respective particles X _j ⁱ is randomly generated within [-v _max , v _max ], v _max is the moving speed of the particle, and is set to 20% of the search range.

[Equation 1]

Where particles X _j ⁱ represent the correction voltage, N is the number of particles, i represents the number of repetitions, and k represents the index for the particles.

In the method of improving the MPPT efficiency of a solar inverter in partial shading due to the influence of clouds or the like, the present invention is characterized in that in step (c), the velocity and position (or correction voltage) In response to the request.

[Equation 2]

Where w is the inertia load, c1, c2, Pbk is the best value for each kth particle, and Gb is the best value among all particles.

Further, the present invention is a method for improving MPPT efficiency of a solar inverter in partial shading, wherein w is 1.2, and c1 and c2 are 2 and 1.5, respectively.

Further, the present invention is a method for improving the MPPT efficiency of a solar photovoltaic inverter in partial shading, characterized in that, in the step (d), the mutant particle group is obtained by the formula (3).

[Equation 3]

Where x ⁱ _r1 , x ⁱ _r2 , x ⁱ _r3 are randomly selected three particles from N particles of the i-th generation of the population of particles, r1, r2 and r3 are values between 1 and N, Value, K and F are mutation factors, rnd is a random value randomly generated between 0 and 1, and CR is a random variable.

Further, the present invention is characterized in that, in the method of improving the MPPT efficiency of a solar inverter in partial shading, K and F are respectively 0.5 and 0.7, and CR is 0.8.

In addition, the present invention relates to a computer-readable recording medium on which a program for performing MPPT efficiency improvement method of a photovoltaic inverter at partial shading is recorded.

As described above, according to the MPPT efficiency improvement method of the solar inverter at partial shading according to the present invention, the maximum power point is followed by starting randomly from the whole voltage through the differential evolution and particle cluster optimization (DEPSO) The efficiency improvement effect that always follows the maximum power point can be obtained even if the shade or the like occurs in all regions.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of a configuration of a solar power generation system for practicing the present invention; FIG.
2 is a circuit diagram of an equivalent circuit of a solar cell according to an embodiment of the present invention.
FIG. 3 is a characteristic curve of a solar cell according to an embodiment of the present invention. FIG. 3 (a) is a VI characteristic, and FIG.
4 is a circuit diagram of a configuration for MPPT control of a photovoltaic power generation system according to an embodiment of the present invention;
5 is a circuit diagram of an MPPT control apparatus of a photovoltaic power generation system according to an embodiment of the present invention.
6 is a table showing the operation of the maximum power point tracking method of the P & O method of the solar inverter according to an embodiment of the present invention.
7 is a graph showing a solar cell VP characteristic curve and an operating point in the P & O method of tracking the maximum power point of a solar inverter according to an embodiment of the present invention.
FIG. 8 is a flow chart illustrating a method for improving MPPT efficiency of a solar photovoltaic inverter in partial shading according to an embodiment of the present invention. FIG.
9 is a graph illustrating characteristics of PSO and DE coupling according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the drawings.

In the description of the present invention, the same parts are denoted by the same reference numerals, and repetitive description thereof will be omitted.

First, the entire configuration of a solar power generation system for carrying out the present invention will be described with reference to FIG.

1, the entire configuration of a solar power generation system for practicing the present invention includes a solar cell array 10, an inverter 20, a control device 30, and a power system 40 .

Here, the solar cell array 10 is for generating electricity by condensing sunlight incident from the outside, and silicon and a composite material are usually used mainly. Specifically, the solar cell array 10 uses a p-type semiconductor and an n-type semiconductor in combination, and utilizes a photoelectric effect to generate electricity by receiving sunlight. Most of the solar cell arrays 10 are formed of large-area P-N junction diodes, and the electromotive force generated at the opposite ends of the P-N junction diode is connected to an external circuit. The minimum unit of the solar cell array 10 is referred to as a cell. Actually, the solar cell is rarely used as it is. This is because the voltage required from one cell is very small, about 0.5V, compared to several tens of V or several hundreds of V, which is necessary for practical use. Therefore, a plurality of unit solar cells can be connected in series or parallel . In addition, when the solar cell array 10 is used outdoors, it is subjected to various harsh environments. Therefore, a plurality of cells are used as a package in order to protect a plurality of cells connected with a necessary unit capacity in a harsh environment.

The inverter 20 integrates the DC power received in the parallel group in the solar cell array 10 into one DC power and converts it into AC power for use as commercial power. The AC power output from the inverter 20 is supplied to the load of the consumer through the power system 40.

The control device 30 is an apparatus that is installed in the inverter 20 and controls the inverter 20. The control device 30 controls the power system 40 through an algorithm that tracks the maximum power point MPP of the solar cell or the solar array 10, So that the maximum generated power is transmitted.

Next, the configuration of the solar cell of the solar cell array 10 will be described with reference to Fig.

The constituent block of the solar cell array 10 is a solar cell, and as described above, it is basically a p-n junction semiconductor that directly converts light energy into electricity. 2 is an equivalent circuit of a solar cell.

The current-voltage characteristic of the solar cell is expressed by the following equation (1).

[Equation 1]

Where I and V are each a solar cell output current and voltage, I ₀ is the diode is the saturation current, q is a charge amount, A is the diode material factor, k is the Boltzmann's constant, T is the absolute temperature, R _S and R _SH The series resistance and shunt resistance of the solar cell. Here, the value of R _SH is so large that the end of equation (1) can be ignored to simplify the analysis. The solar cell array 10 is composed of many solar cells connected in parallel with the series, so that the output current and voltage of the solar cell array 10 have sufficient values for the system connection conditions. In consideration of the above-mentioned simplification, the output current-voltage characteristic of the solar cell array 10 is expressed by Equation 2, where n _p and n _s are the serial and parallel connection numbers of the solar cell.

&Quot; (2) "

Among the current-voltage characteristics, the open circuit voltage V _OC and the short-circuit current I _SC are important. The power generated at both points is zero. V _OC can be expressed as Equation (3) by deriving from Equation (1) when the current flowing through the solar cell is 0, that is, I = 0, while ignoring the shunt resistor R _SH . The short-circuit current I _SC is the current when V = 0 and is almost equal to the photocurrent I _L.

&Quot; (3) "

&Quot; (4) "

The maximum power develops at the current-voltage characteristic point where the product of V and I is the maximum. This is the MPP and is unique as in FIGS. 3A and 3B. Fig. 3A shows the voltage-current curve, and Fig. 3B shows the voltage-power curve. MPP is the highest point in Fig. 3B.

Two important factors to be considered in tracking MPP are solar radiation and temperature. These two factors have a great influence on the characteristics of the solar cell as shown in Equations (1) and (2). As a result, the MPP is constantly changing during the day, and why MPP is constantly being tracked and ensuring that the maximum active power is obtained from the panel.

The photocurrent changes in proportion to the solar radiation. As the solar radiation increases, the short circuit current (I _SC ) increases accordingly. In contrast, the effect on the open circuit voltage (V _OC ) is less affected by the change in current depending on the irradiation dose.

A configuration for MPPT control of a photovoltaic power generation system according to an embodiment of the present invention will be described with reference to FIGS. 4 and 5. FIG.

As shown in FIG. 4, it is composed of a solar cell array, a DC-link capacitor, and a controlled current source replacing the power converter.

As shown in FIG. 5, the MPPT controller (MPPT P & O) generates the reference voltage V _ref by the MPPT algorithm. That is, the MPPT control unit (MPPT P & O) receives the PV voltage V _pv and the PV current I _pv and outputs the reference voltage V _ref . The difference (?) From the actual PV direct-current voltage (V _pv ) is calculated for the reference voltage (V _ref ), and the calculated difference is supplied to the proportional integral gain (PI). The difference between the output and the actual PV direct current (I _pv ) becomes the reference control value of the current source and is input to S1.

That is, in Fig. 5, Σ is a summator (Summer), and outputs a value obtained by subtracting the value of the input signal of the sign from the value of the input signal of the + sign, out of the two input signals. Further, the output of the summer SIGMA in Fig. 5 is input to a limiter, and a limiter designates an upper limit set value and a lower limit set value. If the input value is higher than the upper limit setting value, the upper limit setting value is output. If the input value is lower than the lower limit setting value, the lower limit setting value is output. The range of the triangular wave inputted to the comparator connected later is limited.

The output of S1 in Fig. 5 is input to S1 in Fig. 4, S1 becomes a PWM input, and a switching circuit (for example, the gate of the IGBT) is driven to perform a boost operation. This leads to the MPP.

In particular, the reference voltage generated by the MPPT control unit (MPPT P & O) is converted into a current reference, like the control block (circuit) shown in FIG. In other words, the error between the reference voltage and the actual DC voltage (the output voltage of the solar cell array) is supplied by its value, the DC link capacitance and the proportional gain according to the sampling period. The output of this gain is subtracted from the current of the solar cell module and the result is the reference current for the controlled current source.

That is, S1 in Fig. 5 is the PWM drive signal output for driving the IGBT which coincides with I _ref and I _pv , and is denoted by S1 in Fig. In a general MMPT controller, only the voltage control is performed by using the difference between the MPPT output and the PV voltage as the reference voltage. Preferably, in the present invention, current control is performed to control the current source with the difference between the reference voltage and the PV current as the reference current.

The maximum power point tracking method of the P & O method of the solar inverter according to an embodiment of the present invention will now be described with reference to FIGS. 6 to 9. FIG.

The basic principle of P & O MPPT is to _measure the solar cell output power (P _pv [n]) after controlling the voltage of the solar cell output voltage (V _pv ) The maximum power point is followed by raising or lowering the voltage V _pv ^{+ in} the direction in which the output is increased in comparison with the output power P _pv [n-1]. A brief summary of this method is shown in the table of FIG.

7 shows the PV output characteristics of the solar cell array and the movement of the operating point by P & O MPPT. In Fig. 7, when the first operating point is A, the solar cell array voltage is V _A, and the solar cell output power at this time is P _A. Assuming that the next reference voltage is V _B , the output power at this time is P _B , and the operating point is located at point B. Here, since P _B > P _A and V _B <V _A , ΔP _pv > 0 and _{ΔV pv} <0 become Case 3 in the table of FIG. That is, the next reference voltage becomes V _C smaller than V _B by ΔV. When the operating point moves to C, P _C > P _B and V _C < V _B, so that Case 3 in the table of FIG. 6 is obtained. The next reference voltage is V _D. If the operating point is D, then P _D <P _C and V _D <V _C , which corresponds to case 4 in the table of FIG. The next reference voltage is V _{C, which} is larger than V _D by ΔV.

If the operating point is again C, P _C > P _D , V _C > V _D , which corresponds to case 1 in the table of FIG. 6, and the next reference voltage becomes V _{B which} is larger by ΔV than V _C. Since P _B <P _C and V _B > V _C, it corresponds to Case 2 in the table of FIG. 6, and the next reference voltage becomes V _C smaller than V _B by ΔV.

Therefore, the operating point appears repeatedly: A → B → C → D → C → B → C. The method of determining the next reference voltage according to the polarities of _{ΔV pv} and ΔP _pv is the P & O method. As a result, in the case where there is no variation in the irradiation dose in FIG. 7, the operating point is changed between points B and D, Power Point).

Next, a method for improving the MPPT efficiency of the solar inverter at partial shading according to an embodiment of the present invention will be described in more detail with reference to FIG.

As shown in FIG. 8, the local maximum power point is followed by a P & O (Perturbation and Observation) method.

To this end, first, the correction voltage is initialized (S10). The correction voltage refers to a voltage that increases or decreases when the maximum power is followed by the P & O method. That is, the P & O method is a method of correcting a voltage value following the maximum power point.

Next, the current voltage Vpv (k) and the current Ipv (k) are measured (S21). Here, k represents the current time or the current measured difference. When the current voltage and the current are measured, they are multiplied to calculate the current power Ppv (k) (S22).

Next, the voltage increment is calculated (S23). The current voltage increment DELTA D (k) is calculated by the following equation (6).

&Quot; (6) &quot;

? D (k) = C 占 sign (? D (k-1))

Where C is an incremental constant, preferably less than one. sign is either +1 or -1 indicating a positive or negative number. ΔD (k-1) is the previous voltage increment.

Next, the current power Ppv (k) is compared with the previous power Ppv (k), and the sign of the voltage increment? D (k) is determined according to the result (S24, S25).

Next, the next correction voltage D (k) (or D (k + 1)) is set (S26). That is, it is increased or decreased by the voltage increment DELTA D (k) to set the next correction voltage.

Then repeat the above procedure. Basically, MPPT is performed by P & O method, and MPP converges to an arbitrary point.

Next, it is determined whether the average power value Avg (? Ppv) during a predetermined time interval is smaller than the set reference value e (S27) when the maximum power point converges to an arbitrary point and the change of the current power Ppv is small. If it is small, it performs differential evolution and particle swarm optimization (DEPSO, differential evolution and particle swarm optimization). DEPSO combines PSO (Particle Swarm Optimization) and DE (Differential Evolutionary Optimization).

If a power point larger than the maximum power point Ppv (k) found previously through the DEPSO is found, the previous maximum power point follow-up process (S21 to S27) is repeated with the found power point. That is, if the value of J (Gbest), which is the output of Gbest calculated in the DEPSO process, is larger than P (k), which is the power followed by the P & O process, the Gbest value found in DEPSO is set as a new MPP, .

Next, in order to perform the DEPSO process, the group of particles and their velocities are initialized (S31).

As shown in the following Equation (7), a group of particles is initialized. Where the particles X _j ⁱ represent the correction voltage.

&Quot; (7) &quot;

Where N is the number of individuals (particles) and i is the number of repetitions (or evolutionary households). The number of repetitions i is incremented by one and repeated until the set value. Here, k represents the kth particle among all the individual particles. It differs from k in the P & O process.

Also, the velocity of the initial particles is randomly generated within [-v _max , v _max ]. v _max means the speed of movement of the particles and is set to 20% of the search range.

&Quot; (8) &quot;

Next, it is determined whether to perform particle cluster optimization (PSO) or differential evolution optimization (DE) (S32). That is, if the number of repetitions is an odd number, the PSO process (S41 to S48) is performed, and if it is an even number, the DE process (S51 to S59) is performed. The number of repetitions is the number of evolutionary households and is indicated by i.

First, we explain the process of particle community optimization (PSO).

The velocity and position (or correction voltage) of each particle are calculated (S41). Equation 9 represents the velocity, and Equation 10 represents the new position value or correction voltage to be searched.

&Quot; (9) &quot;

&Quot; (10) &quot;

In Equation (9), w is a predetermined value as the inertial load. Preferably, the inertia load w is 1.2.

In addition, c1 and c2 are constants, preferably 2 and 1.5, respectively. Pbk is the best value for each kth particle, and Gb is the best value among all the particles. Here, a good value represents a position having the highest power value, i.e., a correction voltage.

Next, the fitness J is calculated by measuring the correction voltage of each particle (S42).

The fitness Jk is calculated for the N particles generated in the equation (10). Where Jk is the degree of junction for the kth particle and is the position of the kth particle, ie, the power value at the corrected voltage. At this time, it is set to the correction voltage, and it is a power value measured at that time.

Next, it is determined whether the re-initialization condition is satisfied. If the re-initialization condition is satisfied, initialization step S31 is performed to reinitialize. At this time, the re-initialization condition is determined by the following equation.

&Quot; (11) &quot;

Here, J (X _i ) or J (X _{i + 1} ) represents a previous position value and a new position value (i.e., correction voltage), respectively, and? P is a predetermined threshold value.

Next, the optimum position Pbest of each particle and the total optimum position Gbest are updated (S44). That is, for each particle, if the fitness for the newly generated position vector X _k ⁱ is better than the fitness for the previous optimal position for each particle, replace the highest value P bk for each particle with the newly changed value. If the fitness of the individual optimum position Pbk is better than the fitness of the total optimum position Gbi, this value is substituted.

Where Pbk is the solution with the best fit as the kth particle is iterated and Gbi is the solution with the best fit for the ith iteration.

Next, the repetition number i is increased (S61). That is, optimization is performed for the next generation. Also, when the optimum value is not obtained or the set number of repetitions is not reached. Steps S41 to S44 to search for optimization by moving each particle according to the velocity of the particles are repeatedly performed (S62).

If the optimum value is found or the set number of repetitions reaches, the optimum value is set and the process ends (S62, S63). Here, the optimal value means that the Gbest value is newly updated.

That is, the correction voltage D (k) is set to the total optimum position Gbest and the P & O process is performed in advance (S64). At this time, if the fitness (or power) of the calculated total optimum position Gbest is smaller than the power Ppv (k) of the power point determined in the P & O process, the P & O process is no longer performed (S63).

Hereinafter, the differential evolution optimization (DE) process will be described in detail.

First, arbitrarily three particles x ⁱ _r1 , x ⁱ _r2 , and x ⁱ _r3 are selected from N particles of the i-th generation defined in Equation (7) (S51). Where r1, r2, and r3 are values between 1 and N, and are randomly selected values.

Next, a mutation vector is generated for each particle according to Equation (12) (S52). Here, K and F are mutation factors, preferably values between 0 and 2, more preferably values between 0.5 and 0.7, respectively.

&Quot; (12) &quot;

Next, an experimental vector U ⁱ _k is generated for each particle according to Equation (13). Here, rnd is a random value randomly generated between 0 and 1, and CR is a random variable, and 0.8 is used in the present invention.

&Quot; (13) &quot;

Here, W _k ⁱ is a mutation vector of each particle X _k ⁱ .

Next, the fitness J (U ⁱ _k ) is calculated for the newly generated N test vectors U ⁱ _k (S54). That is, the test vector U ⁱ _k is set as the correction voltage, and the power is measured to calculate the fitness. In other words, experimental vectors are a group of particles containing mutations.

Next, the re-initialization condition as shown in Equation (11) is judged (S55). If the condition is satisfied, the initialization step S31 is performed and reinitialized.

Next, Gbest is calculated and updated (S56).

If the following Equation (14) is satisfied, the solution having the best fitness is updated to Gbest.

&Quot; (14) &quot;

Next, a step S61 of increasing the number of repetition times is performed to perform an optimization operation for the next generation, or if a total optimum position Gbest which is higher than the optimum point obtained in the P & O process exceeds the set number of repetition times or is obtained, Perform the P & O process again.

Next, the effect of the present invention will be described in more detail with reference to FIG.

In the present invention, it is necessary to find the value of the voltage that gives the maximum output in the part for finding the power optimum point Vmpp. DEPSO is a method for collectively searching for optimal values by using several points as initial values. That is, N candidate voltages are generated as shown in Equation (7), and then a maximum output voltage is calculated by substituting the generated N candidate voltages into a mathematical model, and the most excellent value is found as a final output.

9 (a) shows the VP characteristic curve and the maximum power point of the most ideal solar cell, and FIGS. 9 (b), (c) and (d) VP characteristic curve.

That is, when the shade is not working or ideally operated, the characteristics of the module are as shown in FIG. 9 (a) and one point having the same maximum value.

However, when the module is shaded, several poles are generated when the I-V curve characteristic of the PV module is shown in FIGS. 9 (b), (c), and (d). In this system, there are many algorithms to find the maximum point. Many algorithms fall into the local minimum, and the global minimum can not be found. In particular, since the PSO algorithm has the property that all the particles converge in the Gbest direction, there is no function that can escape from the Gbest value when the local minimum is small. In order to improve this, it is possible to increase the probability of finding a global minimum by searching for a completely new point by creating a mutation by combining with DE.

Although the present invention has been described in detail with reference to the above embodiments, it is needless to say that the present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the spirit of the present invention.

10: solar cell array 20: inverter
30: control device 40: power system

Claims (9)

A method for improving the MPPT efficiency of a solar inverter in partial shading of strings and arrays of solar panels,
(a) following the maximum power point according to the P & O process, following the maximum power point until the current power converges to a predetermined point and is smaller than a predetermined first threshold value;
(b) generating a population of particles of N particles by composing the correction voltage as particles, and randomly generating the speed of each particle;
(c) updating the velocity of each particle to find a moving position, calculating a fitness at a position of each particle, and calculating or updating an optimal position and a total optimum position for each particle according to the fitness;
(d) randomly selecting at least three particles in the population of particles, generating a mutation vector for the selected particles, generating a population of mutant particles containing a mutation vector according to the random variable, Calculating or updating a total optimum position that is the best;
(e) repeating the steps (c) and (d), and repeating the steps (a) and (d), wherein the number of repetitions exceeds a preset number of times, And performing the step (a) when an optimal position is detected, wherein the MPPT efficiency improvement method of the solar photovoltaic inverter at the partial shading is performed.
The method according to claim 1,
Wherein the position of each particle in the particle group is set as a correction voltage, and the fitness of each particle is set to a power measured when the correction voltage is a position of each particle. The MPPT efficiency improvement of the solar inverter in partial shading Way.
The method according to claim 1,
If the ratio of the fitness by the current position to the fitness by the previous position is larger than the predetermined second threshold value in the step (c) or (d) and b) repeating steps a) and b) to repeat the MPPT efficiency of the photovoltaic inverter.
The method according to claim 1,
In the step (a), the current voltage and the current are measured to calculate the current power, the voltage increment is calculated, the voltage increment is added to the current voltage to calculate the correction voltage of the next turn, And calculating the power of the rotation of the photovoltaic device and repeating the calculation to obtain the power change.
The method of claim 3,
Wherein the sign of the voltage increment is determined according to a result of comparing the current power with the previous power in the step (a).
The method according to claim 1,
In step (b), the population and velocity of the particles are initialized according to the following equation: V _j ⁱ is the velocity of each particle X _j ⁱ and is randomly generated within [-v _max , v _max ] v _max Is the moving speed of the particles and is set to 20% of the search range. A method of improving MPPT efficiency of a solar inverter in partial shading.
[Equation 1]

Where particles X _j ⁱ represent the correction voltage, N is the number of particles, i represents the number of repetitions, and k represents the index for the particles.
The method according to claim 6,
Wherein the speed and position (or correction voltage) of each particle in the step (c) are updated by the following equation (2).
[Equation 2]

Where w is the inertia load, c1, c2, Pbk is the best value for each kth particle, and Gb is the best value among all particles.
The method according to claim 6,
Wherein in the step (d), the mutant particle group is obtained by the formula (3).
[Equation 3]

Where x ⁱ _r1 , x ⁱ _r2 , x ⁱ _r3 are randomly selected three particles from N particles of the i-th generation of the population of particles, r1, r2 and r3 are values between 1 and N, Value, K and F are mutation factors, rnd is a random value randomly generated between 0 and 1, and CR is a random variable.
A computer-readable recording medium having recorded thereon a program for performing a method of improving MPPT efficiency of a solar inverter in partial shading according to any one of claims 1 to 8.

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